Modified Iterative BP-CNN Decoder under Correlated Noise with Symmetric α-stable Distributions

Senlin Li, Sihui Zheng, Jingwen Zhang, Xiang Chen, Zesong Fei

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Recently, an iterative belief propagation-convolutional neural network (BP-CNN) decoder has been proposed to process the low-density parity-check (LDPC) decoding under correlated noise. However, in many practical scenarios, correlated noise may have extra special characteristics, such as impulse. Therefore, when used in such scenarios, there will be some space for the performance improvement of the BP-CNN decoder, since its loss functions cannot make full use of the special characteristics of correlated noise. Fortunately, the impulsive property of correlated noise can be effectively described by the symmetric α-stable (SαS) distribution model. Thus, we propose a novel loss function to train a well-behaved CNN model under correlated noise with SαS distributions. In order to take advantage of the features of SαS distributions captured by CNN, the proposed loss function involves a probability density function (PDF) estimation of the residual noise and a similarity detection. The similarity detection uses the Kullback-Leibler (KL) divergence method to compare the similarity between the estimated PDF and the Gaussian distribution. In the BP-CNN decoder, the residual noise is defined as the difference between the actual noise and the estimated noise. The effectiveness of our modifications for the BP-CNN decoder will be demonstrated with simulation results.

Original languageEnglish
Title of host publicationICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728123455
DOIs
Publication statusPublished - Dec 2019
Event2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019 - Chongqing, China
Duration: 11 Dec 201913 Dec 2019

Publication series

NameICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019

Conference

Conference2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019
Country/TerritoryChina
CityChongqing
Period11/12/1913/12/19

Keywords

  • BP
  • CNN
  • LDPC
  • PDF estimation
  • SαS distribution

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Li, S., Zheng, S., Zhang, J., Chen, X., & Fei, Z. (2019). Modified Iterative BP-CNN Decoder under Correlated Noise with Symmetric α-stable Distributions. In ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019 Article 9172958 (ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSIDP47821.2019.9172958